Dynamic Characteristic Analysis of Robot's Wrist Force Sensor using Correlation Wavelet Method

摘要

In the dynamic analysis of robot's wrist force sensor, one of the most important steps is to extract the accurate Impulse Response Function (IRF) or Frequency Response Function (FRF) from the input and the output signals of the sensor. In this paper, a novel correlation wavelet method for extracting the IRF of wrist force sensor is presented. Based on the dynamic model of the wrist force sensor, we simulate its dynamic characteristic in two cases when robot impacts with the environments and works in a noisy circumstance. The correlation wavelet method is then used to extract IRF and FRF of the sensor model. The simulation results show that compared with the traditional FFT method, correlation wavelet method exhibits obvious advantages over FFT method, and the accuracy of the results is greatly improved. Correlation wavelet method is a new and effective method for dynamic analysis of robot's wrist force sensor as well as other sensors.